Abstract
This article introduces the use of an Ordinal Probit Regression Model to predict emergency response rates in the Fire Department of New York City (FDNY) when data are of the count-type variety and ordinal. The main objective of this article is to model the effects of boroughs, emergency incident types, and the volume of emergency incidents (counts) on response rates for the years 2010-2016. The model framework discusses the model selection criteria when the proportional odds assumptions for ordinal models are no longer valid, and a model in which scale effects are allowed to vary among emergency incident types is preferred. This statistical insight can be used by elected officials and city agencies to evaluate FDNY's emergency response availability, capability, and operational performance in order to improve emergency services in the five boroughs.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
